Blog
Straight from the lab.
Notes, ideas, and field reports on data & AI, straight from the engagements we run on Snowflake.

What a Snowflake Migration Actually Costs (And What Drives the Number)
Anyone who quotes a firm migration price before seeing your environment is guessing. But the cost is not unknowable: it is the sum of a few clear drivers, from the source system to the pipeline count to governance. Here is what moves the number, and how to bring it down.

How to Choose a Snowflake Partner: A Buyer's Checklist
Certifications are the floor, not the answer. The traits that separate a good Snowflake partner from a painful one rarely make the pitch deck: who builds with your team, who stays accountable after go-live, and who prices to finish rather than to bill. A practical checklist to take into every conversation.

Snowflake Is Now the Control Plane for the Agentic Enterprise
Snowflake began as a data platform, but the rise of agentic AI demands a governed control plane that unifies trusted data, business context, model choice, security, and workflows. This piece explains why Snowflake is positioning itself as that operating layer for the agentic enterprise.

From Constrained to Everywhere: Snowflake as the Foundation for Data Intelligence
Snowflake changed the economics of data, turning what was once constrained, slow, and gated into something elastic, governed, and accessible across the enterprise. As AI collapses the distance between questions and answers, Snowflake becomes the place where you talk to your data and move from insight to action faster than ever.

From Hours to Outcomes: How AI Changed the Economics of Services
At Viewnear, we do not sell hours or headcount. We design outcomes. As a pure-play Snowflake partner, we see clearly that AI has shifted where value is created, moving expertise upstream into steering solutions, orchestrating agents, and owning results.

Separation With Purpose: How Modern Teams Keep Apps Fast and Analytics Scalable
PostgreSQL and Snowflake were built for different kinds of work. With Snowflake Postgres, teams can now run transactional and analytical workloads in the same data cloud, without blurring responsibilities or sacrificing performance.

The Center of Software Work Is Moving, and Data + AI Make It Obvious
As AI and agents take over more of the mechanical implementation work, the middle of building software gets thinner. The real leverage shifts to intent, context, definitions, and ownership, because fast execution without clarity just creates fast mistakes.

How Viewnear Is Using Snowflake Openflow to Build the Next Generation of Data Workflows
Snowflake Openflow, powered by Apache NiFi, gives Viewnear the control, flexibility, and speed to move and prepare data for analytics and AI. It blends visual workflow design with modern engineering standards so our teams build scalable, governed pipelines faster than ever.

From LLMs to AI Agents: Why Snowflake Cortex Signals a New Era for Enterprise AI
As business leaders, we have all seen the hype around large language models. But the shift to AI agents, powered by Snowflake Cortex, is where the real business value begins.

Quiet Steps Toward an AGI-Ready Data Cloud
Artificial general intelligence no longer feels like science fiction, but even the smartest models will stumble without disciplined, trustworthy data. This article outlines the mindset shifts business leaders need, shows how Snowflake quietly smooths the path, and explains why Viewnear favors small, well-governed wins over grand, risky bets.

From SQL to Gen-AI: A First Look at Snowflake Cortex AISQL
Snowflake's Cortex AISQL functions let you run large language model tasks such as classification, extraction, translation, and even image Q&A directly in SQL. Here is what it means for data teams, how it works in practice, and where we at Viewnear see the biggest opportunities.

Just Back from Snowflake Summit 2025: What Stood Out, What Got Us Thinking, and What's Next
Viewnear attended Snowflake Summit 2025 in San Francisco, and beyond a roadmap full of exciting updates, what stood out were the thoughtful conversations, the clear direction the platform was heading, and how those shifts align with the way we help clients build smarter, faster, and more future-ready data solutions.

Why Snowflake's Compute-Storage Architecture Actually Matters for Your Data Strategy
Understanding Snowflake's architectural decisions is not just technical curiosity. It is the foundation for optimizing performance, controlling costs, and building scalable data solutions.

Understanding Zero-Copy Cloning: Snowflake's Most Underutilized Feature
Zero-copy cloning sounds too good to be true until you understand the mechanics. Here is how this feature works and why it should be part of every data team's toolkit.

Why Every Data Team Should Pay Attention to Snowflake's AI Strategy
From a front-row seat watching Snowflake's AI evolution, this is not just another vendor adding ML features. It is a fundamental shift that will change how we build and deploy AI applications.

The Integration Challenge Every BI Team Faces (And How We Solve It)
Connecting Snowflake to your favorite BI tools should not feel like rocket science. After dozens of implementations, here are the patterns that work and the pitfalls that waste time.

The Data Warehouse Transformation I've Been Watching Unfold for Five Years
When I started recommending Snowflake to clients, many were skeptical about cloud data warehousing. Today, those same organizations cannot imagine going back to traditional systems, and here is why this transformation matters.

The AI Assistant That Actually Understands Your Data (And Why That Matters)
Snowflake Cortex Agents are not just another chatbot feature. After implementing them across multiple client environments, I have seen how they are transforming the way business users interact with data, and it is more profound than I initially expected.
Let's stand up a lasting data & AI practice.
Tell us where the organization stands (migrating, scaling, or shipping AI) and we'll map the fastest path to use cases in production, run by in-house teams.
